ObjectiveTo investigate the concentration of residual chlorine in drinking water supplies in refugee camps, South Sudan, March–April 2013.MethodsFor each of three refugee camps, we measured physical and chemical characteristics of water supplies at four points after distribution: (i) directly from tapstands; (ii) after collection; (iii) after transport to households; and (iv) after several hours of household storage. The following parameters were measured: free and total residual chlorine, temperature, turbidity, pH, electrical conductivity and oxidation reduction potential. We documented water handling practices with spot checks and respondent self-reports. We analysed factors affecting residual chlorine concentrations using mathematical and linear regression models.FindingsFor initial free residual chlorine concentrations in the 0.5–1.5 mg/L range, a decay rate of ~5x10-3 L/mg/min was found across all camps. Regression models showed that the decay of residual chlorine was related to initial chlorine levels, electrical conductivity and air temperature. Covering water storage containers, but not other water handling practices, improved the residual chlorine levels.ConclusionThe concentrations of residual chlorine that we measured in water supplies in refugee camps in South Sudan were too low. We tentatively recommend that the free residual chlorine guideline be increased to 1.0 mg/L in all situations, irrespective of diarrhoeal disease outbreaks and the pH or turbidity of water supplies. According to our findings, this would ensure a free residual chlorine level of 0.2 mg/L for at least 10 hours after distribution. However, it is unknown whether our findings are generalizable to other camps and further studies are therefore required.
In response to rapid urbanization throughout the global South, urban and peri-urban slums are expanding at an alarming rate. Owing to inadequate financial and institutional resources at the municipal level, conventional approaches for safe water provision with centralized treatment and distribution infrastructure have been unable to keep pace with rapidly growing demand. In the absence of alternatives to centralized systems, a global public health emergency of infectious water-related diseases has developed. Alternative decentralized water treatment systems have been promoted in recent years as a means of achieving rapid health gains among vulnerable populations. Though much work with decentralized systems, especially in urban environments, has been at the household level, there is also considerable potential for development at the community level. Both levels of approach have unique sets of advantages and disadvantages that, just as with treatment technologies, may make certain options more appropriate than others in a particular setting. Integrating community, government and other relevant stakeholders into the process of systems development and implementation is essential if the outcome is to be appropriate to local circumstances and sustainable in the long term.
Waterborne illnesses are a leading health concern in refugee and internally displaced person (IDP) settlements where waterborne pathogens often spread through household recontamination of stored water. Ensuring sufficient chlorine residual is important for protecting drinking water against recontamination and ensuring water remains safe up to the point-of-consumption. We used ensembles of artificial neural networks (ANNs) to probabilistically forecast the point-of-consumption free residual chlorine (FRC) concentration and to develop point-of-distribution FRC targets based on the risk of insufficient FRC at the point-of consumption. We built ANN ensemble models using data from three refugee settlements and found that the risk-based FRC targets generated by the ensemble models were consistent with an empirical water safety evaluation, indicating that the models accurately predicted the risk of low point-of-consumption FRC despite all ensemble forecasts being underdispersed even after post-processing. This demonstrates the usefulness of ANN ensembles for generating risk-based point-of-distribution FRC targets to ensure safe drinking water in humanitarian operations.
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